jiaxiang-cheng / PyTorch-LSTM-for-RUL-Prediction
PyTorch implementation of remaining useful life prediction with long-short term memories (LSTM), performing on NASA C-MAPSS data sets. Partially inspired by Zheng, S., Ristovski, K., Farahat, A., & Gupta, C. (2017, June). Long short-term memory network for remaining useful life estimation.
RepositoryStats indexes 584,353 repositories, of these jiaxiang-cheng/PyTorch-LSTM-for-RUL-Prediction is ranked #241,441 (59th percentile) for total stargazers, and #535,930 for total watchers. Github reports the primary language for this repository as Python, for repositories using this language it is ranked #43,970/116,326.
jiaxiang-cheng/PyTorch-LSTM-for-RUL-Prediction has Github issues enabled, there are 2 open issues and 0 closed issues.
There have been 1 release, the latest one was published on 2021-06-29 (3 years ago) with the name LSTM for RUL Prediction.
Star History
Github stargazers over time
Watcher History
Github watchers over time, collection started in '23
Recent Commit History
0 commits on the default branch (master) since jan '22
No recent commits to this repository
Yearly Commits
Commits to the default branch (master) per year
Issue History
Languages
The only known language in this repository is Python
updated: 2024-11-21 @ 03:39am, id: 363314671 / R_kgDOFae97w